A clinical scoring system for colon cancer risk could help physicians identify which patients at average-risk for colon cancer could potentially skip a colonoscopy and instead be screened with a less-invasive method. The researchers suggest that this approach could increase the uptake and efficiency of colorectal cancer (CRC) screening. The cross-sectional study is published in Annals of Internal Medicine (2015; doi:10.7326/M14-1720).

Several screening tests are proven effective and are recommended for detecting colorectal cancer, yet screening is still underused, costly, and inefficient. Not all average-risk patients have the same risk for colorectal cancer. Risk stratification could potentially enable physicians to tailor screening based on a patient's risk for colorectal cancer.

Researchers studied a convenience sample of 4,460 patients scheduled to undergo their first screening colonoscopy in the Midwest. A clinical score was given based on the patient's complete health data and presence of the five most common risk factors for CRC: age, sex, waist circumference, cigarette smoking, and family history.

The data showed that patients classified as low-risk did, in fact, have far fewer advanced adenomas compared with patients classified as high-risk. The authors suggest that patients at lower risk for cancer would be able to have a less invasive test (sigmoidoscopy, occult blood tests), while higher-risk patients would need a colonoscopy.

The overall prevalence of advanced neoplasia was 9.4%. The study classified patients as very low risk (1.92% of the patients), low risk (4.88%), intermediate risk (9.93%), and high risk (24.9%). The corresponding risk for advanced neoplasm for very low risk patients was 1.65%, 3.31% for low risk patients, 10.9% for intermediate risk patients, and 22.3% for high risk patients.

An accompanying editorial (2015; doi:10.7326/M15-1677) by Chyke A. Doubeni, MD, MPH, of the University of Pennsylvania Perelman School of Medicine in Philadelphia cautioned that the score should not be used for choosing the type of screening test the person at average risk should undergo. However, a sensitive algorithm may have a role in choosing appropriate follow-up for a patient with a negative screening result.